Resource Allocation

Resource allocation research focuses on optimizing the distribution of limited resources—computational power, bandwidth, energy—to maximize efficiency and fairness across diverse applications. Current research emphasizes developing sophisticated algorithms, including deep reinforcement learning, graph neural networks, and dynamic programming, to address complex, real-time resource allocation problems in areas like federated learning, edge computing, and wireless networks. These advancements are crucial for improving the performance and scalability of various systems, from mobile communications to large-scale AI training, and for ensuring equitable access to resources.